Why it’s time to take learning personally

Personalisation has hit consumer technology hard, and it’s changing the way we process content. It’s time for L&D to catch up, says Caroline Walmsley.

The story of who we are and what we do is increasingly one that’s being told by the choices we make on our digital devices. From the minute we wake up to the minute we go to sleep – and if you’re a sleep app user, the minutes in-between as well – our daily lives are mediated by mobile digital technology.

Even when our phones or tablets are sitting idle, apparently ‘off’, they are pumping data about who and where we are into the Cloud. This information is logged and analysed by the consumer app providers who we open up our lives to, and who use that data to draw inferences about our behaviour and that of everyone around us.

The TV programmes we watch on demand, the holidays we browse for, the books we read, the social media updates we send – all our consumer choices and lifestyle habits are blended into a series of stochastic probabilities that our behaviour will favour a certain path, and content providers feed us suggestions for our next set of choices accordingly.

The potential value locked up in these digital footprints is the great driver of the information economy. ‘Our’ personal data, which organisations capture to mine and repurpose for insights into our behaviour, and to provide us new products and services that fit our consumer patterns, is arguably today’s most precious and powerful business resource.
This personalisation process is reciprocal: we give away information about our behaviour, but in doing so we help shape the development of new solutions which go on to affect our subsequent actions. What we do changes the app, but the app also changes us. The prime, pioneering example of this process is Amazon’s ‘Recommended for you’ feature, which becomes more precise the more frequently it is used, and was conceived with the vision of being able to serve you up your next confirmed purchase – before you’ve even realised you want it.

Personalisation such as this has become standard practice in the past 20 years since its innovation by the supermarket retail industry in the form of loyalty cards. There is now a greater expectation from individuals for tailored content based on behaviours and preferences across other areas of their lives – work included.

The shifts in consumer behaviour this process has triggered have been profound. The things we read and view online – the things we learn from – all have to measure up to match the experiences provided by the most advanced social media tools and consumer platforms. Like it or not – and the pressure to keep up with the retail, media and electronics giants can be exhausting for less extravagantly funded L&D departments – the digital media ecology has created a new kind of learner who doesn’t just prefer but expects their media to be highly relevant and targeted to their needs and preferences, mobile, and available anywhere on demand. It goes even further than that.

The new learner literally will not – cannot – meaningfully engage with content that doesn’t make this effort to fit their expectations, or fails to meet their complex and personally specific requirements. The new learner will (almost) always turn to Google or YouTube for their learning needs, long before they’ll turn to their company’s LMS.

What does this tell us about what today’s cutting edge learning technology should look like? For learners it means SaaS, it means mobile, it means instant. It means not having to wait for an administrator to confirm learner choices or for a training module or course to be deployed to fill a gap in our skills or knowledge.

Delivering this kind of experience requires a next gen LMS that knows the learner already, can learn about them based on their actions, and supplies them with a range of suitable options whenever they need it, and dependent on what they’re doing in the moment.

The essential ingredient for personalised learning content is data. Learner capability, usage, feedback and behavioural info tracked through a next generation LMS can be sifted to understand and quantify then model and anticipate learner choices and deliver them appropriate learning specific to their learning need and journey.

A lack of this data is what has traditionally held L&D from being able to offer such a level of custom service. After all, according to the 70:20:10 framework, only the 10% of formal learning served through an old-style LMS could be captured. Masses of value locked up in the 90% of learning data that happens outside the standard LMS was all but inaccessible, with flat ‘Click Next’ e-learning courses providing too few interaction and response points to gather enough intelligence to make informed predictions. But L&D is already developing powerful next generation tools to fix this – the fightback is underway.
Thanks to the options for data capture and retrieval enabled by new learning technologies from next generation LMSs, to smart diagnostic tools, machine learning and the Experience API, this all changes. The xAPI in particular turns even our informal, on-the-job learning experiences into useful, retrievable information, finally giving L&D a big enough part of the picture to make meaningful inferences about learners’ future requirements and preferences.

Once a greater, data-driven view of individual learning is established, a new way of thinking about learning and development is required. In order to raise organisational skill levels generally, the learning activity needs to occur at the level of the individual learner, looking closely at who they are, what they need to know and how they can best learn it. This microscopic view of the learner is the key to achieving real change at the macro, organisational level.

There is understandable reticence in L&D to adapt to some of this thinking. Partly it’s to do with terminology: it’s important to remember that your learners are learners, no matter how much you may start to think of them as ‘consumers’ in order to develop learning content that really speaks to them and meets their learning need.

More important however is to understand the material changes that a world of personalised learning content afford us, and how the learner – having shaped their ideal learning content through the interpretation of their past choices – is in truth anything but a passive consumer.

In fact, with truly personalised learning provision the individual’s learning journey itself becomes the major contributing factor in the production of further learning content: The app changes them, and then they change the app.

This article first appeared in e.learning age magazine.



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